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BIG PHYSICS, BIG QUESTIONS –

Watson supercomputer looks for genetic heart danger

The Jeopardy!-winning supercomputer teaming up with a powerful individual heart simulator to diagnose someone's chances of sudden cardiac arrest

By Paul Marks

Snapshot of an arrhythmia

(Image: IBM)

SUDDEN cardiac arrests kill someone every 5 seconds. Now the fact-finding power of Watson, IBM’s Jeopardy-winning supercomputer, is being harnessed to help assess the genetic risk behind the condition.

Unlike a heart attack, which happens because of a blockage in blood flow to the heart muscle, sudden cardiac arrest can be caused by combinations of hard-to-predict factors, including irregular electrical disturbances that upset heart rhythm, genetic factors and the side effects of drugs. So it can appear to strike out of nowhere.

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Sudden cardiac arrest can appear to strike out of nowhere. Very often, the first symptom is death

So he and his colleagues at the Lawrence Livermore National Laboratory in California and the University of Rochester in New York have turned to supercomputers to help them identify the risk factors leading to fatal arrhythmia. Their algorithms use CT and MRI scans to create detailed 3D computer models of the heart. The simulations mimic the electrical and mechanical behaviour of a beating heart down to the level of cells – allowing the team to recreate the conditions that cause problems. It lets them simulate what happens when you add drugs to the heart cells.

But a crucial component has been missing&colon; genetics. No matter how good the graphics produced by the lab’s IBM Sequoia supercomputer, if a patient’s background genetic susceptibility to sudden cardiac arrest is not factored in, the risk prediction could be way off.

US oncologists are already using Watson to help them personalise cancer treatment, so Reumann knew where to turn for help. Watson is now mining the medical literature to look for interactions between specific genes that humans could never spot, but which could help us understand how they contribute to sudden cardiac arrest. These findings will then be plugged back into the 3D model to see what effect they have.

Ultimately, the plan is to be able to use scans of a heart, recordings of its electrical activity, and gene sequence data, to predict someone’s risk of sudden cardiac arrest. If they are at risk, they could be prescribed antiarrhythmic drugs, for example.

Andrew Grace at Papworth Hospital in Cambridge, UK, who studies how genes affect heart arrhythmias, says the strong genetic component in sudden cardiac arrest makes Watson’s contribution valuable. “Whether you are going to drop dead or not is in your genes,” he says.

This article appeared in print under the headline “Watson explores heart mysteries”